Scalable Collaborative Filtering Recommendations Using Divisive Hierarchical Clustering Approach
نویسنده
چکیده
Recommender system is the most important technology in e-commerce .It is used to suggest valuable products for the customer and improve their business intelligence. Collaborative filtering is a technique which is used to suggest information from similar kinds of users. Scalability is the biggest challenge in collaborative filtering recommender system. When more number of users is increasing in the site the system should provide accurate recommendations for the super user. We use divisive hierarchical clustering approach to overcome this scalability issue when more number of users increases in terms of neighborhood size.
منابع مشابه
A Imputed Neighborhood based Collaborative Filtering System for Web Personalization
Recommender system is the most important technology in Ecommerce .It is used to suggest valuable products for the customer and improve their business intelligence. Collaborative filtering is a technique which is used to suggest information from similar kinds of users. Scalability is the biggest challenge in collaborative filtering recommender system. When more number of users is increasing in t...
متن کاملUse of Semantic Similarity and Web Usage Mining to Alleviate the Drawbacks of User-Based Collaborative Filtering Recommender Systems
One of the most famous methods for recommendation is user-based Collaborative Filtering (CF). This system compares active user’s items rating with historical rating records of other users to find similar users and recommending items which seems interesting to these similar users and have not been rated by the active user. As a way of computing recommendations, the ultimate goal of the user-ba...
متن کاملHandling Cold Start Problem in Recommender Systems by Clustering Demographic Attribute
Recommender engines have become immensely important in recent years because a large number of people depend on internet to browse options out of a vast set of choices. Different websites implement recommender systems using different techniques such as content-based filtering, collaborative filtering or hybrid filtering. Recommender systems face various challenges like scalability problem, cold ...
متن کاملیک سامانه توصیهگر ترکیبی با استفاده از اعتماد و خوشهبندی دوجهته بهمنظور افزایش کارایی پالایشگروهی
In the present era, the amount of information grows exponentially. So, finding the required information among the mass of information has become a major challenge. The success of e-commerce systems and online business transactions depend greatly on the effective design of products recommender mechanism. Providing high quality recommendations is important for e-commerce systems to assist users i...
متن کاملA New WordNet Enriched Content-Collaborative Recommender System
The recommender systems are models that are to predict the potential interests of users among a number of items. These systems are widespread and they have many applications in real-world. These systems are generally based on one of two structural types: collaborative filtering and content filtering. There are some systems which are based on both of them. These systems are named hybrid recommen...
متن کامل